IBM Cloud Pak for Data Accelerator

IBM accelerators for these business areas and industries

• General:

  Staff Optimization:	Manpower management with mathematical optimization
  Contact Center Insights:	Insights using AI on structured and unstructured data.

• Energy suppliers and service providers:

  Energy Demand Planning:	Support of planning with mathematical optimization
  Payment Risk Predicition:	Using Data Science to identify potentially defaulting customers
  Attrition Prediction:	Identify candidates for customer programs using Data Science

• Insurances

  Claims Leakage:	Optimization of damage payments
  Loss Estimation:	Use of (satellite) imagery for AI-supported damage assessment after natural disasters
  Reduce Weather Risks:	Use of weather data for early detection of severe weather events.

Get to know the individual accelerators and their use cases:

Staffing Optimization:     

Challenges

• Determination of required staff was often delegated to local managers in the past
• Reduction of possible overhangs through adjusted staff planning
• Staff must still deliver good service to the customer

Solution

• Optimizing staffing levels by determining the best distribution of staff per area/location/machine, etc.

Contact Center Insights:

Challenge

• Customer questions and complaints reach the company through diverse, non-connected channels
• Customer inquiries and complaints about services and products are delivered in a variety of ways and formats, including text and voice
• Manual understanding of content, relationships, and patterns is cumbersome, slow, and expensive

Solution

• AI-powered understanding of customer inquiries across boundaries of channel, format, and time

Energy Demand Planning

Challenge

• Producing too much energy wastes valuable resources; too little can cause blackouts
• In particular, accurately predicting renewable energy yields is problematic

Solution

• Combining traditionally separate processes for forecasting, optimization, and planning into a single, integrated solution
• Predefined, proven algorithms with very good forecast accuracy

Payment Risk Prediction

Challenge

• Late or missed payments impact the financial health of the organization
• Understanding the context of missed payments can help avoid them
• Professional customers expect 360° view of the customer

Solution

• Identification of customers, with the ability to take timely action

Attrition Prediction

Challenge

• In deregulated markets, new players have a hard time identifying the right customers willing to switch
• Acquiring a new customer vs. retaining an existing customer is about six times more expensive

Solution

• Identify customers willing to switch
• Improve understanding of AI model to increase accuracy

Claims Leakage

Challenge

• Unclaimed damage sums are a problem in the insurance industry
• Inefficient processes cost insurance companies $30 billion worldwide

Solution

• Reducing leakage can typically reduce claim costs by 5-10%.
• Context in claim data can provide clues as to which claims are potentially not being handled optimally

Loss Estimation

Challenge

• Increasing amount of large claims
• Difficulty in estimating losses and thus the loss amount

Solution

• AI-supported analysis of satellite images (before-after)
• Automatic detection of damage
• Automatic calculation of damage amount based on assumptions

Reduce Weather Risks

Challenge

• After major losses, e.g. natural disasters, a lot of data is available in different forms and formats that have to be used for analysis

Solution

• Platform for analysis, visualization and prediction of a wide variety of data in any quantity and structure

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